Title :
Vector morphology and iconic neural networks
Author :
Wilson, Stephen S.
Author_Institution :
Applied Intelligent Syst. Inc., Ann Arbor, MI, USA
Abstract :
Mathematical morphology involves the geometrical analysis of shapes and textures in images. Methods of generalizing morphology are presented, and it is shown that all common image-based operators are instances of two fundamental operators where voting logic is at a pivotal point. Another generalization leads to vector operators. A sequence of vector morphology operations is similar to a multiple-layer iconic neural network. In morphology, a new operator called a weighted rank order filter becomes apparent. It is noted that massively parallel, bit serial computer architectures are the most effective way to realize the various operations discussed
Keywords :
computerised picture processing; filtering and prediction theory; neural nets; parallel architectures; bit serial computer architectures; computerised picture processing; geometrical analysis; iconic neural networks; parallel processing; shapes; textures; vector morphology; voting logic; weighted rank order filter; Algorithm design and analysis; Automation; Computer vision; Educational institutions; Neural networks; Radiography; Shape; Solids; Surface morphology; Surface topography;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on